> The value of knowing syntax, APIs, and framework conventions approaches zero. An LLM can look these up faster than you can remember them.

The irony here is that although pointing out quite well how people may have made incorrect judgment calls due to what comes down to personal experience at various times, this aspect is also down to personal experience.

An LLM can look these up and is still getting them wrong, or it can get them right but still pick the wrong conventions to use. More importantly though, LLM code assistants will not always be performing lookups, you cannot assume the same IDE and tool configuration profile for everyone. You cannot even assume that everyone's using an IDE with an embedded chatbot.

> Consider what happens when you build software professionally. You talk to stakeholders who do not know what they want and cannot articulate their requirements precisely. You decompose vague problem statements into testable specifications. You make tradeoffs between latency and consistency, between flexibility and simplicity, between building and buying. You model domains deeply enough to know which edge cases will actually occur and which are theoretical. You design verification strategies that cover the behaviour space. You maintain systems over years as requirements shift.

I'm not sure why he thinks current LLM technologies (with better training) won't be able to do more and more of this as time passes.

If you are thinking about not reading the syntax of AI generated code, i.e vibe coding on production software, just show this simple case study. [0]

For transparency in future incidents, I now expect that post-mortems like this one [0] would go along the lines of: "An AI code generator was used, it passed all the tests, we checked everything and we still got this error."

There is still one fundamental lesson in [0]: English as a 'programming language' cannot be formally verified and probabilistic AI generators can still be the cause of perfect-looking code being the cause of an incident.

This time the engineers will have no understanding of the AI generated code itself.

[0] https://sketch.dev/blog/our-first-outage-from-llm-written-co...